Triple

T186212
Position Surface form Disambiguated ID Type / Status
Subject Shibuya, Tokyo, Japan E3985 entity
Predicate contains P35 FINISHED
Object Ebisu
Ebisu is a fashionable Tokyo neighborhood known for its upscale dining, craft beer scene, and convenient access via Ebisu Station near Shibuya.
 E29485 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ebisu | Statement: [Shibuya, Tokyo, Japan, contains, Ebisu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ebisu
Context triple: [Shibuya, Tokyo, Japan, contains, Ebisu]
  • A. Kato
    Kato is the nickname of Kato Svanidze, who was the first wife of Soviet leader Joseph Stalin.
  • B. Nisshoki
    Nisshoki, more commonly known as the Hinomaru, is the national flag of Japan featuring a red sun disc centered on a white field.
  • C. Matsubara
    Matsubara is a suburban city in Japan’s Kansai region, located within Osaka Prefecture and forming part of the Osaka metropolitan area.
  • D. Mori
    Mori is a Japanese surname shared by various notable individuals across fields such as entertainment, sports, and politics.
  • E. Dededo
    Dededo is a major village and commercial center in northern Guam, known for its large population and role as a key residential and retail hub on the island.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ebisu
Triple: [Shibuya, Tokyo, Japan, contains, Ebisu]
Generated description
Ebisu is a fashionable Tokyo neighborhood known for its upscale dining, craft beer scene, and convenient access via Ebisu Station near Shibuya.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ebisu
Target entity description: Ebisu is a fashionable Tokyo neighborhood known for its upscale dining, craft beer scene, and convenient access via Ebisu Station near Shibuya.
  • A. Kato
    Kato is the nickname of Kato Svanidze, who was the first wife of Soviet leader Joseph Stalin.
  • B. Nisshoki
    Nisshoki, more commonly known as the Hinomaru, is the national flag of Japan featuring a red sun disc centered on a white field.
  • C. Matsubara
    Matsubara is a suburban city in Japan’s Kansai region, located within Osaka Prefecture and forming part of the Osaka metropolitan area.
  • D. Mori
    Mori is a Japanese surname shared by various notable individuals across fields such as entertainment, sports, and politics.
  • E. Dededo
    Dededo is a major village and commercial center in northern Guam, known for its large population and role as a key residential and retail hub on the island.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a25497e2f08190a040f8c6e1842643 completed Feb. 28, 2026, 2:36 a.m.
NER Named-entity recognition batch_69a2594809288190b3d3b1283e7e0d00 completed Feb. 28, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69a35e9fb768819087282451ec8051b0 completed Feb. 28, 2026, 9:31 p.m.
NEDg Description generation batch_69a35f07ea20819087d55fab8b6ab53f completed Feb. 28, 2026, 9:32 p.m.
NED2 Entity disambiguation (via description) batch_69a35f70a7808190a3620493eb8238e3 completed Feb. 28, 2026, 9:34 p.m.
Created at: Feb. 28, 2026, 2:40 a.m.